[Numpy-discussion] "import numpy" performance

David Cournapeau cournape@gmail....
Mon Jul 2 15:33:21 CDT 2012

On Mon, Jul 2, 2012 at 8:17 PM, Andrew Dalke <dalke@dalkescientific.com> wrote:
> In this email I propose a few changes which I think are minor
> and which don't really affect the external NumPy API but which
> I think could improve the "import numpy" performance by at
> least 40%. This affects me because I and my clients use a
> chemistry toolkit which uses only NumPy arrays, and where
> we run short programs often on the command-line.
> In July of 2008 I started a thread about how "import numpy"
> was noticeably slow for one of my customers. They had
> chemical analysis software, often even run on a single
> molecular structure using command-line tools, and the
> several invocations with 0.1 seconds overhead was one of
> the dominant costs even when numpy wasn't needed.
> I fixed most of their problems by deferring numpy imports
> until needed. I remember well the Steve Jobs anecdote at
>   http://folklore.org/StoryView.py?project=Macintosh&story=Saving_Lives.txt
> and spent another day of my time in 2008 to identify the
> parts of the numpy import sequence which seemed excessive.
> I managed to get the import time down from 0.21 seconds to
> 0.08 seconds.

I will answer to your other remarks later, but 0.21 sec to import
numpy is very slow, especially on a recent computer. It is 0.095 sec
on my mac, and 0.075 sec on a linux VM on the same computer (both hot
cache of course).

importing multiarray.so only is negligible for me (i.e. difference
between python -c "import multiarray" and python -c "" is
statistically insignificant).

I would check external factors, like the size of your sys.path as well.


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